HIV-1 envelope sequence-based diversity measures for identifying recent infections

Alexis Kafando, Eric Fournier, Bouchra Serhir, Christine Martineau, Florence Doualla-Bell, Mohamed Ndongo Sangaré, Mohamed Sylla, Annie Chamberland, Mohamed El-Far, Hugues Charest and Cécile L Tremblay

PLOS ONE, 2017, vol. 12, issue 12, 1-24

Abstract: Identifying recent HIV-1 infections is crucial for monitoring HIV-1 incidence and optimizing public health prevention efforts. To identify recent HIV-1 infections, we evaluated and compared the performance of 4 sequence-based diversity measures including percent diversity, percent complexity, Shannon entropy and number of haplotypes targeting 13 genetic segments within the env gene of HIV-1. A total of 597 diagnostic samples obtained in 2013 and 2015 from recently and chronically HIV-1 infected individuals were selected. From the selected samples, 249 (134 from recent versus 115 from chronic infections) env coding regions, including V1-C5 of gp120 and the gp41 ectodomain of HIV-1, were successfully amplified and sequenced by next generation sequencing (NGS) using the Illumina MiSeq platform. The ability of the four sequence-based diversity measures to correctly identify recent HIV infections was evaluated using the frequency distribution curves, median and interquartile range and area under the curve (AUC) of the receiver operating characteristic (ROC). Comparing the median and interquartile range and evaluating the frequency distribution curves associated with the 4 sequence-based diversity measures, we observed that the percent diversity, number of haplotypes and Shannon entropy demonstrated significant potential to discriminate recent from chronic infections (p

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0189999

DOI: 10.1371/journal.pone.0189999

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